An Online Feedback Motion Planning and Control Strategy for UAVs in Wind

An Online Feedback Motion Planning and Control Strategy for UAVs in Wind. Doshi, A., Singh, S. P. N., & Postula, A. In Australian Conference on Robotics and Automation, 2012.

Paper abstract bibtex

This paper describes a model reduction strategy for obtaining a computationally efficient prediction of a fixed-wing UAV performing waypoint navigation under steady wind conditions. The strategy relies on the off-line generation of time parametrized trajectory libraries for a set of flight conditions and reduced order basis functions functions for determining intermediate locations. It is assumed that the UAV has independent bounded control over the airspeed and altitude, and consider a 2D slice of the operating environment. We found that the reduced-order model finds intermediate positions within 10% and at speeds of 10x faster than clock-time (even in wind conditions in excess of 50% of the UAV's forward airspeed) when compared against simulation results using a medium-fidelity flight dynamics model. The potential of this strategy for online planning operations is highlighted.

@INPROCEEDINGS{acra.windgustuav.2012,
  author = {A. Doshi and S. P. N. Singh and A. Postula},
  title = {An Online Feedback Motion Planning and Control Strategy for UAVs
	in Wind},
  booktitle = {Australian Conference on Robotics and Automation},
  year = {2012},
  abstract = {This paper describes a model reduction strategy for obtaining a computationally
	efficient prediction of a fixed-wing UAV performing waypoint navigation
	under steady wind conditions.  The strategy relies on the off-line
	generation of time parametrized trajectory libraries for a set of
	flight conditions and reduced order basis functions functions for
	determining intermediate locations.  It is assumed that the UAV has
	independent bounded control over the airspeed and altitude, and consider
	a 2D slice of the operating environment.  We found that the reduced-order
	model finds intermediate positions within 10% and at speeds of 10x
	faster than clock-time (even in wind conditions in excess of 50%
	of the UAV's forward airspeed) when compared against simulation results
	using a medium-fidelity flight dynamics model. The potential of this
	strategy for online planning operations is highlighted.},
  pdf = {doshiAcra12.pdf},
  url = {http://www.araa.asn.au/acra/acra2012/papers/pap147.pdf}
}

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